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International Journal of Scientific and Engineering Research (IJSER) January 17, 2014 Paper Number: I039867 Paper Title: Healthcare Spending and Economic Growth in Saudi Arabia: A Granger Causality Approach Authors: Abdulkarim K. Alhowaish Urban and Regional Planning Department College of Architecture and Planning University of Dammam P.O. Box 2397, Dammam 31451 Saudi Arabia E-mail: [email protected]

Dear Dr. Abdulkarim K. Alhowaish We are pleased to inform you that your paper entitled “Healthcare Spending and Economic Growth in Saudi Arabia: A Granger Causality Approach” has been accepted for publication in International Journal of Scientific and Engineering Research (IJSER), Volume 5, Issue1, January 2014 Edition (ISSN 2229-5518).

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International Journal of Scientific & Engineering Research, Volume 5, Issue 1, January-2014 ISSN 2229-5518

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Healthcare Spending and Economic Growth in Saudi Arabia: A Granger Causality Approach Abdulkarim K. Alhowaish

Abstract— The purpose of this paper is to investigate the relationship between healthcare spending and economic growth in Saudi Arabia and the causal direction between them over the period 1981-2013 using Granger Causality approach. The result from the Granger causality test shows that there is a unidirectional causal relationship running from economic growth to healthcare spending. Economic growth positively Granger cause healthcare spending growth at one percent significant level while healthcare has an insignificant effect on Saudi economic growth. Economic growth as measured by GDP is strongly exogenous and whenever a shock occurs in the system (Saudi economy), healthcare spending must be reduced to maintain the long run relationship. In order to sustain Saudi healthcare system, Saudi health policy makers needs to formulate a long term healthcare policy that de-linking or insulate healthcare spending from current oilrevenue dependency.

Index Terms— Healthcare Spending, Economic Growth, Saudi Arabia, Granger Causality Approach

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1 INTRODUCTION Since the release of the Report of the Commission on [1] Macroeconomics and Health (CMH) in 2001, several countries have evaluated the recommendations in light of their unique country health and socioeconomic contexts and have embarked on steps to implement long-term macroeconomic policies that would secure health as an essential component of socio-economic development planning. Advocates of the positive link between health spending and economic growth projected that, sustained health spending enhances productivity (through better health status of workers) which ultimately promotes economic growth. Thus to these supporters, healthcare spending [2-5] granger causes economic growth, all things being equal. The key deficiency, however, with this linkage stems from the fact that the general consensus is predicated on assumed (not empirically verified) causal relationship between the two variables. As far as search of available literature is concern, there is little of no compelling empirical evidence in support of this view as well as the magnitude of the healthcare spending effects on economic growth. In fact, there is significant empirical evidence in the literature to the effect that the direction of causality between the two variables could also run from economic growth to growth in healthcare spending or the causal effect could be bidirectional. The relationship between health and economic growth has been empirically investigated intensely, although, the [6-12] Moreover, most of empirical studies have evidence is mixed. focused on developed countries by using a panel data analysis. Therefore, a country-specific study on developing countries such as Saudi Arabia is relatively scarce. The goal of this study is to investigate the relative impact of healthcare spending on economic growth in Saudi Arabia. Specifically, this research paper attempts to empirically answer the following questions: Is there a relationship between healthcare spending and economic growth? And, if a relationship exists, what is the direction of causality between these two variables? In other words, this study examines the extent to which a healthcare strategy is a relative growth factor for Saudi Arabia. The rest of the paper is organized as follows: A brief study of previous empirical studies is presented in section 2. An overview of Saudi healthcare spending is presented in section 3. Section 4 provides data and econometric approach used in the study. Empirical findings are discussed in section 5 and the main conclusions are stated in section 6.

2 LITERATURE REVIEW The relationship between healthcare spending and economic growth has been empirically investigated intensely since the publication of the [13] [14] and Newhouse. These two authors seminal papers in Kleiman have argued that there is a strong positive correlation between the healthcare spending and economic growth. On one hand, healthcare spending is hypothesized to be a function of real gross domestic product (GDP). Higher income implies that there is more money to spend on health. A large body of research within health economics indicated that variation in per capita healthcare spending [15-17] could be mostly explained by variations in per capita GDP. [18] indicated that 85% of the scholars in the field of health Fuchs economics agreed that aggregate income is one of the most important factors in explaining healthcare expenditure growth. On the other hand, it is also hypothesized that health is a capital and hence investment on health is an important source for economic growth. Theoretically, health is a determinant of human capital, and labor productivity. So, regarding health spending as an investment in human capital and accordingly the engine of growth, an increase in health spending is [19-22] More healthcare spending is expected to lead to higher income. expected to lead to better health status, which eventually must lead to more labor productivity and more competitive nation and hence more economic prosperity, which implying that the causal relationship between healthcare spending and economic growth may run in either or both directions. As mentioned early, however, the relationship between healthcare spending and economic growth has been empirically investigated [23] intensely, although, the evidence is mixed. For example, Culyer , [24] Hansen and King indicate, in their studies, that there is no long-run relationship between healthcare expenditure and GDP. Devlin and Hansen (2001) examined Granger causality between health expenditure and GDP and showed some (mixed) evidence that indeed there might be bi-directional causality between health spending and [25] support for the existence of a long run income. Bukhari and Butt relationship between GDP and health expenditure and the exogeneity [26] revisits the question whether health of GDP in Pakistan. Hartwig capital formation stimulates GDP growth in rich countries applying the panel Granger-causality framework. His results do not lend support to the view that health capital formation fosters long-term economic [27] growth in the OECD area. Mehrara and Musai support the existence of a long run relationship between GDP and health expenditure in Iran.

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International Journal of Scientific & Engineering Research, Volume 5, Issue 1, January-2014 ISSN 2229-5518 [28]

Recently, Sghari and Hammami examined the causality between the real per capita health care expenditure and real per capita GDP in 30 developed countries. Their findings indicate that bi-directional causality relationship is predominant. The reviews of relevant literature validate the positive relationship between healthcare spending and economic growth with direction of causality running from economic growth to growth in healthcare spending without any feedback effects. To the best of the authors’ knowledge, no study yet has been carried out in case of Saudi Arabia in finding out the casual relationship between healthcare spending and economic growth. 3 HEALTHCARE SPENDING IN SAUDI ARABIA The Healthcare sector in Saudi Arabia is primarily managed and financed by the Government through the Ministry of Health (MOH) and number of semi-public organization who specifically operate hospitals and medical services for their employees. With a total of 244 hospitals (33, 277 beds) and 2,037 primary health care (PHC) centers, MOH comprised approximately 60% of the total healthcare services in Saudi [29] Arabia. The private sector also contributes to the delivery of health care services, especially in major urban centers, with a total of 125 hospitals (11, 833 beds) and 2,218 dispensaries and clinics. The private sector comprised about 21% of healthcare services in the [29] country. The Saudi Healthcare sector is structured to provide a basic platform of healthcare services to all citizens and expatriates working within the public sector with full and free access to all public healthcare [30-31] services. During the last four decades, however, spending on healthcare [29] services increased from 2.8% in 1970 to 6.9% in 2011. According to [32] Colliers International Healthcare report , between 2005 and 2008 Saudi government allocated approximately SAR 23.5 billion per annum with a cumulative amount of SAR 94 billion investment in the healthcare sector. However, in 2010 and 2011 there was a substantial increase in the healthcare budget which increased from SAR 30 billion (6.3% of total government budget) in 2008 to SAR 52 billion in 2009 (11% of total government budget) and to SAR 61.2 billion in 2010 (11.3% of total government budget). The budget allocation was further increased to SAR 68.7 billion (11.8% of total government budget) in 2011, a cumulative allocation of SAR 113 billion in last two years [32] compared to SAR 94 billion in the previous four years. Saudi healthcare spending increased by 8.7% per year in real terms between 2000 and 2011, this was followed by an increase of 12.4% in [33] 2012. Changes in the ratio of health spending to GDP are the result of the combined effect of growth in both GDP and health expenditure. Between 1981 and 2012, the annual average growth in healthcare spending in real terms was about 1.3%, nearly 2.5 times greater than [33] the growth rate in GDP per capita. Saudi government devoted on average 3.7% of its GDP to healthcare spending in 2011, down slightly from the peak of 4.5% reached in [34] 2001. This share, however, remains well below many developed and developing nations. For example, the United State had the highest share of its GDP allocated to healthcare services in 2011 (17.9%), followed by Netherlands (12%), Germany (11.1%), New Zealand (10.1%), Japan (9.3%), Jordan (8.4%), Turkey (6.7%), Iran (6.0%) and Egypt (4.9%). In terms of healthcare spending to GDP ratio, however, Saudi Arabia ranked 173 among 192 of the world’s healthcare [34] system. It is estimated that, government spending in healthcare services is expected to increase to SAR 174 billion in 2017 due to the growing demand drivers for [35] One of major drivers for healthcare services in Saudi Arabia. healthcare services is the population growth. The Central Department [36] estimates the total Saudi of Statistics and Information (CDSI) Arabian population will reach 31.6 million by 2016, of which 22.8 million will be Saudi nationals. The expanding population, coupled with rising average income, will continue to feed demand for healthcare services. With an estimated population growth rate of 2.2% over the next four years coupled with the increasing of life expectancy in one hand and increasing occurrence of “lifestyle diseases” on the other hand, the supply of healthcare facilities struggles to keep pace with the burgeoning population, a situation recognized by the Saudi

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government who has recently introduced initiatives to encourage the [31,35] private sector to match the shortfall of public healthcare services. 4 DATA AND ECONOMETRIC APPROACH 4.1 Data The main objective of this study is to investigate the causal relationship between healthcare spending and economic growth in Saudi Arabia. The dataset employed consists of annual data on healthcare spending and real GDP from 1981 to 2013. Data on healthcare spending and real GDP (in local currency – Saudi Riyal) were obtained directly from [33] the Saudi Arabian Monetary Agency (SAMA) database. All variables are expressed in natural logarithms which could reduce the problem of heteroscedasticity as log transformation compresses the scale in which [37-38] Table 1 presents summery statistic of the variables are measured. the data and the pairwise correlations of variables show strong and significant correlations between healthcare spending human (𝐥𝐧(𝒉𝒄𝒔)) and economic growth (𝐥𝐧(𝒈𝒅𝒑)) of Saudi Arabia during the 1981 to 2012. Table 1: Summary Statistics and Pairwise Correlation Matrix ln(hcs) ln(gdp) Mean 9.817963 Median 9.688684 Maximum 11.16956 Minimum 9.221280 Std. Dev. 0.551551 Skewness 1.081496 Kurtosis 3.053041 Jarque-Bera 6.436855 Probability 0.040018 Observations 33 Correlation ln(hcs) 1.000000 ln(gdp) 0.948085 Source: Authors estimation using EViews8.

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13.50892 13.31065 14.81886 12.67898 0.652729 0.721067 2.298623 3.536064 0.170669 33 0.948085 1.000000

4.2 Econometric Approach To test the existence of causality, the Granger causality test developed [39] is employed. Basically, this test from the seminal paper of Granger seeks to ascertain whether or not the inclusion of past values of a variable x do or do not help in the prediction of present values of another variable y. If variable y is better predicted by including past values of x than by not including them, then, x is said to Granger-cause y. For this purpose, the following vector autoregressive model of lag order n, VAR (n), is utilized: 𝑛

𝑛

(1)

𝑖=1 𝑛

𝑖=1 𝑛

(2)

𝑖=1

𝑖=1

𝑋𝑡 = 𝛼1 + � 𝜆1𝑖 𝑌𝑡−𝑖 + � 𝛾1𝑖 𝑋𝑡−𝑖 + 𝛿1 𝑍 + 𝜀1𝑡 𝑌𝑡 = 𝛼1 + � 𝛾1𝑖 𝑋𝑡−𝑖 + � 𝜆1𝑖 𝑌𝑡−𝑖 + 𝛿2𝑍 + 𝜀2𝑡

Where (𝑋𝑡 ) represents economic growth, (𝑌𝑡 ) represents healthcare spending and (𝑍) is a set of seasonal dummies exogenously included to capture any seasonal effects. A test of joint significance of the lagged values constitutes the Granger causality test. More specifically, healthcare spending is said to Granger-cause economic growth if some (𝜆𝑖 ≠ 0) in equation 1. By the same logic, economic growth is Grangercausing healthcare spending if one or more(𝛾𝑖 ≠ 0). An important issue here is the choice of the optimal lag length as all inference in the VAR is naturally based on the chosen lag order, i.e. the number of lags chosen in the above equations have a significant impact on the decision to reject or accept the null hypothesis. Hence, the Schwarz [40] Information Criterion (SIC) is employed to determine the optimal lag length(𝑛). 5

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EMPIRICAL RESULTS

International Journal of Scientific & Engineering Research, Volume 5, Issue 1, January-2014 ISSN 2229-5518 It is well documented that Granger causality tests require the use of [41-42] Thus, stationary variables, i.e. variables integrated of order zero. as a preliminary step to the analysis, the order of integration of the variables is determined. Two standard unit root tests are employed— [43] [44] the augmented Dickey-Fuller (ADF) test and Phillips–Perron (PP). Under the ADF and PP tests, the series is assumed to be nonstationary. Hence, failure to reject the null hypothesis implies that the time series has a unit root. The ADF test checks for serial correlation by adding lagged values of explanatory variables. While the PP test uses a non-parametric method to take care of serial correlation in the error term without adding a lagged difference term. Table 1 presents the results of the ADF and PP unit root test, which implies that both variables healthcare and economic growth (𝑙𝑛𝑔𝑑𝑝 & 𝑙𝑛ℎ𝑐𝑠) are stationary at their first difference level - I(1). Therefore, the VAR model is used to investigate the causal relationship between the two variables. Table 1: Unit Root Test ADF PP st st Variables 1 1 Level Level difference difference 1.4804 -4.0927 1.0487 -4.0241 LnGDP (0.998) (0.003) (0.996) (0.004) 1.5694 -4.8354 2.1309 -4.8762 LnConst (0.999) (0.000) (0.999) (0.000) Notes: Figures in the parenthesis are the probability value. Source: Authors estimation using EViews8.

Decisi on I(1) I(1)

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length as an optimal lag selection for the VAR model (see Appendix II). Results of causality test are presented in Table 2. Table 2: Granger Causality Test F-Statistic P-Value Causality Lag Length Healthcare ↛ Economic ** 1 0.65038 0.426 Growth Economic Growth ↛ ** 1 21.0254 0.000 Healthcare Healthcare ↛ Economic 2 0.42590 0.657 Growth Economic Growth ↛ 2 9.24570 0.000 Healthcare Healthcare ↛ Economic 3 0.10196 0.958 Growth Economic Growth ↛ 3 4.62245 0.011 Healthcare Notes: 1. The notation Economic Growth ↛ healthcare represents the null hypothesis: Economic growth (GDP) does not Grangercause Healthcare spending. A similar interpretation follows for the reverse test. ** denotes optimal leg length based on (AIC), (SC) and (HQ) 2. Criterion test. Source: Authors estimation using EViews8. From the 𝜒2 -statistics, the null hypothesis that spending in healthcare does not cause or precede economic growth is not rejected. Instead, the Granger causality test lends support to the growth-driven hypothesis, i.e. healthcare spending is largely influenced by economic growth. Thus, a unidirectional causal relationship exists between healthcare spending and economic growth in Saudi Arabia, and the direction of causality is running from economic growth to healthcare spending without any feedback effects. The estimated VAR model is also subjected to a battery of diagnostic tests (see Table 3). These tests imply that the model is well-behaved: the errors appear to be normally distributed non-heteroscedastic and free of autocorrelation.

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technique was It should be noted that the Johansen and Juselius applied to test for the presence of cointegration relationship between the variables but the results revealed that there is no cointegration association between them. Both the trace test and the maximum eigenvalue test were below the 5% critical value, implying no cointegration. Hence, the standard methodology using Granger cause approach is preceded (see Appendix I). Prior to testing for Granger causality relationship, the optimal lag order [46-48] . The maximum number of lags in the VAR model must be chosen is set at 4. All the information criterion procedure tests suggest one lag

Table 3: Diagnostic Tests Test Test Statistic VAR Residual Heteroscedusticity Test (without cross terms) 𝜒2 = 3.457 VAR Residual Heteroscedusticity Test (with cross terms)

𝜒2 = 38.313

VAR Residual Normality Test (Jarqua Bera)

𝜒2 = 1.8857

VAR Residual Serial Correlation LM Test (lags 1 to 12)

Source: Authors estimation using EViews8. 6 CONCLUSIONS This paper investigated the causal relationship between healthcare spending and economic growth in Saudi Arabia over the period 19812013 using econometric analysis approach. The Augmented Dickey Fuller (ADF) test and the Phillips–Perron (PP) test were used to check

LM = 3.457 LM = 4.082 LM = 1.314 LM = 9.198 LM = 2.130 LM = 3.793 LM = 1.931 LM = 4.215 LM = 2.067 LM = 5.925 LM = 6.968 LM = 1.375

P-value 0.126

0.073 0.756 0.484 0.395 0.858 0.056 0.711 0.434 0.748 0.377 0.723 0.204 0.137 0.848

for stationarity of time series of variables under investigation. The Granger causality test was utilized to establish the possible casual relationships among the variables. The unit root test reveals that all the variables were stationary at first difference. These unit root tests yield no evidence of co-integrating vector(s) between series, and thus, no

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International Journal of Scientific & Engineering Research, Volume 5, Issue 1, January-2014 ISSN 2229-5518 long run stable relationship between healthcare spending and economic growth in Saudi Arabia. However, the result from the Granger causality test shows that there is a unidirectional causal relationship running from economic growth to healthcare spending. Economic growth positively Granger cause healthcare spending growth at 1 percent significant level while healthcare has an insignificant effect on Saudi economic growth. In other words, GDP is strongly exogenous and whenever a shock occurs in the system (Saudi economy), healthcare spending must be reduced to maintain the long run relationship. Given the nature of Saudi Arabian economy as oil-resource-based economy, any vulnerability of oil revenues will result in dramatic decrease in healthcare spending. It is well documented that dependency oil-resource countries suffered from a weak and [49-52] These countries are highly undiversified economic base. vulnerable to boom-and-bust economic cycles, both internally and externally. Therefore, in order to sustain Saudi healthcare system, policy makers needs to formulate a long term Saudi healthcare policy that de-linking or insulate Saudi healthcare spending from current oilrevenue dependency. ACKNOWLEDGMENTS I would like to extend my sincere gratitude to Dr. Fahd A. Al-Muhanna for his valuable contribution in revising the manuscript and for his suggestions and comments in preparing this research study.

2.

3.

10. Freeman, D.G. (2003) Is health care a necessity or a luxury? Pooled estimates of income elasticity from US State-level data. Applied Economics, 35(5): 495-502. 11. Sen, A. (2005) Is health care a luxury? New evidence from OECD data. International Journal of Health Care Finance and Economics, 5(2): 147-164. 12. Wang, Z. and Rettenmaier, A.J. (2007) A note on cointegration of health expenditures and income. Health Economics, 16(6): 559578.

13. Kleiman, E. (1974) The determinants of national outlay on health. In: Perlman (Ed.), The Economics of Health and Medical Care. John Wiley & Sons, New York. 14. Newhouse, Joseph P. (1977) Medical-care expenditure: a crossnational survey. Journal of Human Resources; 12: 115-125. 15. Hansen, P., King, A. (1996) The determinants of healthcare expenditure: a cointegration approach. Journal of Health Economics, 15:127–137.

16. Butt, M. S. and I. A. Toor (2005) Determinant of health care expenditures in Pakistan. Pakistan Economic and Social Review, Volume XLIII, No. 1.

REFERENCES 1.

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World Health Organization (2001) Macroeconomics and Health: Investing in Health for Economic Development, Available from: http://www.who.int/whosis/cmh. [Last accessed on 2013 December 4]. Bloom, D. E., Canning, D., & Sevilla, J. (2004). The Effect of Health on Economic Growth: A Production Function Approach. World Development, 1-13. Mayer, D. (2001). The Long term impact of health of economic growth. World Development, 1025-1031.

17. Hall, R.E., Jones, C.I. (2007) The value of life and the rise in health spending. Quarterly Journal of Economics, 122 (1): 39–72. 18. Fuchs, V.R. (1996) Economics, values, and health care reform. American Economic Review, 86 (1): 1–24.

19. Muysken, J., I.H. Yetkiner & T. Ziesemer. (2003) Health, Labor Productivity and Growth, in Growth Theory and Growth Policy. London: Routledge. 20. Arora, S. (2001) Health, Human Productivity, and Long-Term Economic Growth. The Journal of Economic History , 699-749.

4.

5.

Schultz, T. P. (2005). Productive Benefits of Health: Evidence from Low-Income Countries. Economic growth center discussion paper No. 903 . Zon, A. v., & Muysken, J. (2001). Health and endogenous growth. Journal of Health Economics, 169–185.

6.

Parkin, David/McGuire, Alistair/Yule, Brian (1987): Aggregate health care expenditures and national income. Is health really a luxury good? Journal of Health Economics; 6: 109-127.

7.

Roberts, J. (1999) Sensitivity of elasticity estimates for OECD health care spending: analysis of a dynamic heterogeneous data field, Health Economics, 8, 459–72.

8.

9.

Gerdtham, U.G. and M. Lothgren. (2000). On Stationary and Cointegration of International Health Care Expenditure and GDP. Journal of Health Economics, 19: 461-475. Gerdtham, U.-G. and Jonsson, B. (2000) International Comparisons of Health Expenditure: Theory, Data and Econometric Analysis, in Handbook of health economics (Eds) J. P. Newhouse and A. J. Culyer, North Holland/Elsevier, Amsterdam, pp. 11–53.

21. McCoskey, S. K. and T. M. Selden (1998) Health care spendings and GDP: Panel data unit root results. Journal of Health Economics, 17:369-376. 22. Getzen, Thomas E. (2000) Health care is an individual necessity and a national luxury: applying multilevel decision models to the analysis of health care expenditures. Journal of Health Economics; 19: 259-270. 23. Culyer, T.J. (1990) The Internal Market: An Acceptable Means to a Desirable End, Working Papers 067chedp. University of York, Centre for Health Economics. 24. Hansen, P. and A. King (1998), Health care spending and GDP: Panel data unit root results – Comment. Journal of Health Economics, Volume 17, pp. 377-381. 25. Bukhari S.A. and Butt M.S. (2007) The direction of causality between health spending and gdp the case of Pakistan. pakistan economic and social review, 45(1): 125-140. 26. Hartwig, Jochen. (2010) "Is health capital formation good for longterm economic growth? - Panel Granger-causality evidence for OECD countries," Journal of Macroeconomics, Elsevier, 32(1): 314-325.

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27. Mehrara, M. and Musai, M. (2011) The causality between health expenditure and economic growth in Iran, Int. J. Eco. Res., 2(4): 13-19.

41. Hatanaka M. (1996) Time-Series-Based Econometrics: Unit Roots and Cointegration, Oxford University Press.

28. Sghari M.A. and Hammami S. (2013) Relationship between health expenditure and gdp in developed countries. iosr journal of pharmacy, 3(4): 41-45.

42. Engle, R.F. and Granger, C.W.J. (1987) Co-integration and errorcorrection: Representation, estimation and testing. Econometrica, 55(2): 987-1008.

29. Ministry of Health (MOH), Statistical Year Book – Various Reports. Available from: http://www.moh.gov.sa/. [Last accessed on 2013 December 4].

43. Dickey, D. A., W. A. Fuller. (1981) Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root, Econometrica 49, 1057-1072.

30. Aldossary A, While A, Barriball L. (2008). Health care and nursing in Saudi Arabia. International Nursing Review, 55:125–128.

44. Phillip P.C.B. and Perron P. (1988), Testing for a unit root in time series regression, Biometrika, Vol: 75, 335-346.

31. M. Almalki, G. Fitzgerald and M. Clark. (2011). Health care system in Saudi Arabia: an overview. Eastern Mediterranean Health Journal, EMHJ, 17 (10): 784-793

45. Johansen, S., & Juselius, K. (1990). Maximum Likelihood Estimation and Inference on Cointegration with applications to the Demand for Money. Oxford Bulletin of Economics and Statistics, 52, 169-210.

32. Colliers International Healthcare (CIH) Report. (2012), Kingdom of Saudi Arabia: Healthcare Overview. Available from: http://www.colliers.com/~/media/files/emea/uae/research/ma rket-overview/ksahealthcareoverviewcihq12012.ashx. [Last accessed on 2013 Dec. 12]. th

33. Saudi Arabian Monetary Agency (SAMA), 48 Annual Report, Available from: http://www.sama.gov.sa/. [Last accessed on 2013 December 4].

46. Harris, R. (1995) Using Co-integration Analyses In EconometricModelling. Simon & Schuster International Group. 47. Sims (1972) Role of approximate prior restrictions in distributed lag estimation. Journal of American Statistical Association. 169175 48. Enders, W. (2004), Applied Econometric Time Series. 2nd ed. New York: Wiley.

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34. World Health Organization (2011) National Health Account database, Available from: http://data.worldbank.org/indicator/SH.XPD.TOTL.ZS. [Last accessed on 2013 November 24]. 35. NCB Capital Report (2012), Saudi healthcare spending. Available from: http://www.saudigazette.com.sa/index.cfm?method=home.r egcon&contentid=20121114142767. [Last accessed on 2013 November 19] th

36. Central Department of Statistics and Information, 45 Annual Report, Available from: http://www.cdsi.gov.sa/. [Last accessed on 2013 December 4]. 37. Bhargava, A., Jamison, D. T., Lau, L. J., & Murray, C. J. (2001) Modeling the effects of health on economic growth. Journal of Health Economics , 423–440.

49. Aguiar-Conraria, L. and Y. Wen. (2006) Oil Dependence and Economic Instability, Federal Reserve Bank of St. Louis 2006060A. 50. Gylfason, Thorvaldur, Tryggvi Thor Herbertsson, and Gylfi Zoega (1999) “A Mixed Blessing: Natural Resources and Economic Growth,” Macroeconomic Dynamics 3(6): 204-225. 51. Aguiar-Conraria, L. and Y. Wen. (2007) Understanding the large negative impact of oil shocks, Journal of Money, Credit, and Banking 39(4), 925-44. 52. Aljarrah, M. A. (2008) Non-oil export growth and economic development in Saudi Arabia: a simultaneous equations approach, Majallat dir-s-t al-Khal.j wa-al-Jaz.rah al Arab.yah, 34 (129): 25-44.

38. Greene H. William. (2002) Econometric Analysis (5th Edition) New Jersey: Pearson Education Inc.

39. Granger, C.W.J. (1969) “Investigating causal relations by econometrics models and cross spectral methods”, Econometrica, 37, 424-438. 40. Dickey, D.A. and Fuller, W.A. (1979). Distributions of the Estimators for Autoregressive Time Series with a Unit Root, Journal of the American Statistical Association, 74, 427-31.

APPENDICES Appendix I: Johanson-Juselius Cointegration Test Date: 12/25/13 Time: 12:45 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments IJSER © 2014 http://www.ijser.org

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Trend assumption: Linear deterministic trend Series: LOGGDP LOGHC Lags interval (in first differences): 1 to 1 Unrestricted Cointegration Rank Test (Trace) Hypothesized No. of CE(s)

Eigenvalue

Trace Statistic

0.05 Critical Value

Prob.**

None At most 1

0.284223 0.009833

10.67232 0.306318

15.49471 3.841466

0.2325 0.5799

Trace test indicates no cointegration at the 0.05 level Unrestricted Cointegration Rank Test (Maximum Eigenvalue) Hypothesized No. of CE(s)

Eigenvalue

Max-Eigen Statistic

0.05 Critical Value

Prob.**

None At most 1

0.284223 0.009833

10.36600 0.306318

14.26460 3.841466

0.1890 0.5799

Max-eigenvalue test indicates no cointegration at the 0.05 level

IJSER

* denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values Appendix II: VAR Lag Order Selection Criteria VAR Lag Order Selection Criteria Endogenous variables: LOGGDP LOGHC Exogenous variables: C Date: 12/25/13 Time: 14:04 Sample: 1981 2013 Included observations: 28 Lag

LogL

LR

FPE

AIC

SC

HQ

0 1 2 3 4

-17.16044 50.53085 51.96618 54.66972 56.33121

NA 120.8773* 2.358039 4.055316 2.254874

0.013473 0.000143* 0.000172 0.000192 0.000233

1.368603 -3.180775* -2.997584 -2.904980 -2.737943

1.463761 -2.895303* -2.521797 -2.238878 -1.881526

1.397694 -3.093503* -2.852131 -2.701346 -2.476128

* indicates lag order selected by the criterion LR: sequential modified LR test statistic (each test at 5% level) FPE: Final prediction error AIC: Akaike information criterion SC: Schwarz information criterion HQ: Hannan-Quinn information criterion

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